Reference is hereby made to commonly assigned co-pending U.S. patent applications Ser. No. 09/280,286 filed on even date herewith for IMPROVED METHOD FOR ISCHEMIA DETECTION AND APPARATUS FOR USING SAME in the names of Robert W. Stadler et al., Ser. No. 09/968,454 filed on even date herewith for AXIS SHIFT ANALYSIS OF ELECTROCARDIOGRAM SIGNAL PARAMETERS ESPECIALLY APPLICABLE FOR MULTIVECTOR ANALYSIS BY IMPLANTABLE MEDICAL DEVICES, AND USE OF A SAME in the names Robert W. Stadler et al. Ser. No. 09/280,592 filed on even date herewith for DETERMINATION OF ORIENTATION OF ELECTROCARDIOGRAM SIGNAL IN IMPLANTABLE MEDICAL DEVICES in the names Robert W. Stadler et al.
FIELD OF THE INVENTION
This invention relates to a method and apparatus embodied in an implantable medical device (IMD) or an external medical device (EMD) for monitoring myocardial ischemia of a patient""s heart and optionally applying a therapy to a patient experiencing ischemia.
Further, this invention relates to ways to detect ischemia through cardiac pacing, and during mixed paced and intrinsic cardiac events, and also during blocked bundle branch intrinsic events. (Blocked bundle branch intrinsic events produce electrocardiogram forms similar to paced events. Accordingly, when in the detailed description reference is made to non-standard or paced electrograms, unless otherwise noted, it should be understood that reference is also being made to bundle branch blocked electrograms).
Myocardial ischemia is the leading cause of morbidity and mortality in developed countries. Myocardial ischemia involves oxygen starvation of the myocardium, particularly in the bulky left ventricular wall, that can lead to myocardial infarction and/or the onset of malignant arrhythmias if the oxygen starvation is not alleviated. Although myocardial ischemia is associated with the symptom of angina pectoris, the majority of episodes of myocardial ischemia are asymptomatic or xe2x80x9csilent.xe2x80x9d
Accurate and rapid detection of myocardial ischemia is the first essential step toward reducing morbidity and mortality from this often silent but deadly condition. Without the knowledge of the condition, it cannot be treated. A wide range of therapies are known for the treatment of myocardial ischemia once it is detected, including surgical revascularization, neural stimulation and a variety of biologically active agents or compounds which can remove blood clots, reduce cardiac workload or improve cardiac circulation.
The electrocardiogram (ECG) or electrogram (EGM) of the cardiac cycle detected across sense electrode pairs located on the patient""s skin or in the patient""s body, respectively, is a repetitive waveform characterized by a periodic PQRST electrical activation sequence of the upper and lower heart chambers. The PQRST sequence is associated with the sequential depolarization and contraction of the atria followed by the depolarization and contraction of the ventricles, and successive PQRST complexes are separated by a baseline or isoelectric region. The PQRST electrical activation sequence commences with the P-wave indicative of the depolarization and contraction of the atria and is followed by the QRS complex indicative of the depolarization and contraction of the ventricles. The T-wave at the termination of the ST segment time delay is associated with re-polarization of the ventricles. The PQRST electrical activation sequence with intact A-V activation detected across a sense electrode pair is fairly predictable in shape. The P-wave, R-wave and T-wave events occurring in sequence in the range of normal heart rates are usually readily recognized by visual examination of the external ECG or an EGM recorded by implanted electrodes that are correctly oriented with the depolarization waves. The P-wave and R-wave are readily sensed by sense amplifiers of a monitor or therapy delivery device coupled with appropriately placed sense electrode pairs.
The ST segment of the ECG or EGM is typically close in amplitude to the baseline or isoelectric amplitude of the signal sensed between PQRST sequences, depending on the sense electrode pair location. During episodes of myocardial ischemia, the ST segment amplitude is elevated or depressed (depending on positioning of the ECG or EGM sense electrodes in relation to the heart) from baseline. These ST segment deviations can be readily recognized by visual examination.
The physiological basis of ST segment deviation changes in the presence of cardiac ischemia may be explained by ischemic changes in the action potential of cardiac myocytes. When myocytes become ischemic, the resting potential increases (toward zero), the depolarization slope of the action potential decreases, the plateau decreases in voltage, and the duration of the action potential decreases. These changes result in voltage gradients and an xe2x80x9cinjury currentxe2x80x9d between normal and ischemic myocardium during the resting and plateau phases of the action potential. Because the voltage gradient between the normal and ischemic myocardium is positive during diastole and negative during systole, the isoelectric or baseline signal level and the ST segment signal level of the ECG are displaced in opposite directions during ischemia. The change in the isoelectric or baseline level is not easily detected because the pair of sense electrodes implanted in the patient""s body are AC coupled through filters to the inputs of differential sense amplifiers. However, the disparity between the isoelectric or baseline level and the ST segment may be detected if the isoelectric or baseline point and the ST segment point can be identified.
It has long been a goal in the development of external cardiac monitors and IMDs to be able to automatically detect ST segment deviations from baseline and to accurately determine when the heart is ischemic therefrom so that the patient""s cardiac condition can be assessed and treated both in the clinical setting and while the patient is outside a clinical setting. A wide number of implantable therapy delivery devices and or monitors have been proposed for detecting ischemia and delivering a therapy and/or recording the detected ischemic events in an ambulatory patient. Fundamentally, the algorithms employed in these systems endeavor to automatically sample the amplitude of the ST segment in the PQRST complex in an EGM or ECG signal, compare its absolute amplitude against a threshold and declare an ischemic or normal condition based on the results of the comparison.
In regard to Implantable Medical Devices (IMDs), commonly assigned U.S. Pat. Nos. 5,199,428 and 5,330,507 and U.S. Pat. No. 5,203,326, are incorporated herein by reference, and describe the historical development of electrical stimulation of the carotid and vagus nerves and other nerves to relieve cardiac arrhythmias and angina pectoris associated with myocardial ischemia. Perhaps more important to the background of this invention, they also describe relatively simplistic methods for detecting cardiac ischemia. The ""326 patent also proposes providing backup anti-tachyarrhythmia pacing and cardioversion/defibrillation shock therapies. U.S. Pat. Nos. 5,531,768, 5,497,780, 5,135,004 and 5,313,953, all incorporated herein by this reference, monitor or detect myocardial ischemia and some record data related to ischemic episodes for telemetry out at a later time, to provide therapy or even to set off an alarm.
In these ischemia detection IMDs, the ischemia detection depends entirely or at least in part on the location of a fiducial point in the PQRST sequence, sampling the EGM signal level at a point within the ST segment in the PQRST sequence, and detection an elevated or depressed ST level exceeding a threshold level. Automatic detection techniques are set forth in the above-incorporated ""428 and ""50xe2x80x3 patents that depend on sensing the R-wave, setting an ST segment time window timed from the detected R-wave, sampling the amplitude and/or integrating the amplitude to develop a current event ST signal level, and comparing the current event ST signal level to a threshold signal level that is derived from an average normal ST signal level. In the ""953 patent, a computationally expensive template establishing and matching algorithm is set forth that determines xe2x80x9clxe2x80x9d and xe2x80x9chxe2x80x9d deflection points preceding and following the R-wave of each PQRST sequence as the fiducial point or points. The ST segment signal level is sampled 80 ms after the determined xe2x80x9cjxe2x80x9d point and is compared to the threshold signal level.
In the above-incorporated ""428 patent, it was proposed that the detection of myocardial ischemia be accomplished by also sensing the patient""s coronary sinus blood pH and/or oxygen saturation and comparing each to preset, normal thresholds. The sensors are located in the coronary sinus or a coronary vein to measure the dissolved oxygen and/or the lactic acid level of myocardial venous return blood. The system includes programmable thresholds against which the signals developed by the sensors and the ST segment deviation are compared. When ischemia is confirmed, the disclosed system triggered burst stimulation of selected nerves until the blood gas and/or ST segment variations returned to non-clinical risk levels. However, blood oxygen sensors that perform adequately over a period of chronic implantation have not been perfected, and blood oxygen changes can be due to conditions or physiologic states of the patient other than ischemia.
These prior approaches are also problematic for a number of reasons that contribute to the magnification of the deviation of the sampled ST signal level from the isoelectric level due to factors and conditions other than myocardial ischemia, thus registering too many false positive indications of ischemia to be very useful. Myocardial ischemia can be mistakenly detected due to ST segment changes in the PQRST complex caused by xe2x80x9caxis shiftsxe2x80x9d, electrical noise, cardiac pacing, and high sinus or tachycardia cardiac rates that distort the shape of the PQRST complex. These problems are described, for example, in xe2x80x9cAnalysis of Transient ST Segment Changes During Ambulatory Monitoringxe2x80x9d by Franc Jager et al. at Computers in Cardiology, 1991, Los Alamitos: (IEEE Computer Society Press 1991: 453-456). xe2x80x9cAn Approach to Intelligent Ischemia Monitoringxe2x80x9d by Bosniak et al. in Med. and Bio. Eng. and Comp. 1995. pp. 749-756, and in xe2x80x9cA Compact, Microprocessor-Based ST-Segment Analyzer for the Operating Roomxe2x80x9d by Seven J. Weisner et al. (IEEE Trans. on Biomedical Engineering BME-92, No. 9:642-648.
For detection of axis shifts and eliminating their confounding effects on attempts to establish a reliable ischemia detection system, the Jager algorithm (from his article listed in the preceding paragraph) measures the electrical axis angle and the difference between the ST segment and the isoelectric level over two periods, one immediately after the other, and compares the difference in mean the parameters between these two periods to a threshold. Bosniak et al. use a multistate Kalman filter to look for step changes in ST segment, representing axis shifts. This method is far too complex for current generation implantable devices.
There remains a need for a system capable of automatically and reliably detecting ischemia. Significant advantage can be had if it is able to detect ischemia in any portion of the patient""s heart. Ease of implantation, stability and long term use in ambulatory patients is obviously a consideration. Important also is that such a system reliably and consistently distinguish ischemia from other conditions or physiologic states of the patient. Additionally an indication of the location of the ischemia is useful too.
This can be characterized as a need for such a system for accurately detecting myocardial ischemia through measurements of the cardiac EGM in more than one sensing axis to account for the possible locations of ischemic regions of the heart that is easily implanted and functions reliably over time, even as the heart condition changes.
Also, detection during pacing is problematic due to the non-standard paced electrogram signal, relative to normal non-paced electrogram signals, and a way to employ discoveries about detection of ischemia during such non-standard cardiac electrogram signals needs to be developed, and is taught in this application.
The present invention provides apparatus requirements and algorithmic processes that can be used to satisfy some or all of these needs. It contemplates a more reliable and consistent method and apparatus implementing an algorithm in an IMD which may also be useful for an external medical device for automatically and accurately detecting myocardial ischemia and triggering delivery of a therapy, data storage, and/or diagnostic assistance, as well as processing abilities to filter out bad data from electrocardiogram signals for other purposes as detailed and described within. It is also useful to find which cardiac cycles might have data which would be invalid for one purpose but which would therefore be indicative of a changing physiologic condition. Accordingly, filtering out the xe2x80x9cbad cyclexe2x80x9d information can yield useful indicator data as well from the information contained in what would otherwise be considered invalid cycles.
It is thus an object of the present invention to accurately detect episodes of myocardial ischemia from sense electrodes located on the patient""s skin or in the patient""s body and distinguishing ST segment deviations due to ischemia from ST segment deviations that may be caused by one or more factors other than actual ischemia, including at least electrical noise, xe2x80x9caxis shiftxe2x80x9d, cardiac pacing, and distortion of the PQRST complex due to arrhythmias and high sinus heart rates.
It is a further object of the present invention to accurately detect episodes of myocardial ischemia in this manner from sense electrodes arranged to provide a plurality of sense electrode pair vectors for developing a plurality of vector ECG or EGM signals from substantially the entire heart where ischemia develops.
The collection of electrogram data includes samples taken from portions of the cardiac cycle including portions in a QRS complex, (usually to find the R-wave peak, although this is not necessary in some embodiment); and samples in the ST segment: plus at least a sample in an isoelectric area, usually prior to the QRS complex, although following the T-wave would be acceptable also for finding an isoelectric point for the processes we describe.
At least one or more of the objects are realized in a system providing, in general and preferably, at least one of the following features.
Adaptive noise detection, (i.e., the device will enable parameterizing the waveform, comparing current parameters to expected ranges, updating expected ranges from the current waveform if the majority of parameters are within range, and keeping track of the frequency with which a parameter does not fall within the expected range to adapt to abrupt rhythm changes). With the processes, an algorithm in the apparatus can adapt to accept the heart rhythm of any individual and exclude cardiac cycles that do not fit the normal pattern for such as individual. Our noise detection algorithm is free of thresholds except the number of cycles out of range that constitutes a rhythm change (this is 12 in the most preferred form of the algorithm).
An additional novel feature of the noise detection is its ability to take advantage of multiple, preferably orthogonal, vectors. In other words, rather than check if a parameter is outside of a 1-D allowed range, using our invention we can check if a vector parameter is outside of a multi-dimensional xe2x80x9callowed spacexe2x80x9d.
Adaptation to slow changes in the rhythm of the individual by adjustments to variables we maintain in memory with values for the expected ranges of parameters, and eventual acceptance of abrupt changes in rhythm by automatic broadening of expected ranges.
We have also provided a feature designed to make the signal indifferent to AC noise (typically 50 or 60 Hz) in the ECG signals, because this is the most common frequency of noise in the modern world. In preferred embodiments we set the ECG sample rate at an integer multiple of 50 or 60 Hz and average all ECG measurements over complete cycles of 50 or 60 Hz. Therefore, by sampling at twice the AC frequency, and averaging all measurements over two samples (thus producing a frequency domain xe2x80x9czeroxe2x80x9d at the AC frequency) we essentially eliminate the power frequency noise. This feature may have separable applicability to monitoring body signals generally.
Also, it may be noted that the ST segment measurements are conducted at multiple locations based on rate-adaptive delays from the peak of the R-wave. Therefore, at higher heart rates, the location of the ST measurement is closer to the QRS complex.
Most algorithms base ST segment location on delay from the J point. The J point is difficult to locate algorithmically. The difficulty results in variation in the actual location of measurements. Use of the peak of the R-wave temporal location for finding the places to measure the electrogram signal gives our approach an unusual starting point.
Adaptations to use the invention during pacing are also described.
Preferably, too, the measured ST changes are filtered so that only ST changes that occur at rates that are characteristic of human ischemia are accepted. Since commercial algorithms look at absolute ST deviation, they have trouble with ischemic ST deviations that are superimposed on slow ST drift. Commercial algorithms usually have some filter to exclude the fast xe2x80x9cnoisyxe2x80x9d S changes, but not to remove the slow drift. Our filters get rid of both slow and fast ST deviations. The result of our algorithm is a xe2x80x9crelativexe2x80x9d ST deviation as opposed to an absolute measurements of deviation. Our filters respond to ST changes at physiologic rates (measured empirically), and reject all changes outside this range as noise.
Observation of ST segment changes can take advantage of orthogonal ECG leads with our apparatus. The difference between the ST segment and the isoelectric level can be treated as a 3-dimensional vector, whose position is determined by 3 orthogonal ECG leads. (One could use our teachings for 2- and n-dimensional vectorization of the ST segment variation constraints as well). The temporal evolution of the ST vector is tracked over time for movements that are representative of ischemic changes. This improves the sensitivity of the device, and combines ECG leads so separate processing of each lead vector can be eliminated. This is similar to multidimensional noise detection described earlier in this summary, except that here the orthogonality is applied to the xe2x80x9csignalxe2x80x9d (i.e., the ST change), not the noise. For example, is the ST change vector moving away in space from it""s expected location? At what velocity is it moving? It this movement indicative of ischemia? If the changes are too slow or too fast they will be ignored in preferred embodiments.
Another preferred feature is the detection of axis shifts and removal of their potential confounding effects on ST segment observations. This provides an additional basis for determining good ischemia signals in ST segment analysis for ischemia, and thus good ischemia detection results. Particularly when using the other inventive analysis described herein. Axis shifts occur when postural changes (of the patient) alter the location of the heart with respect to the recording electrodes. They can cause sudden and significant changes in the ST level. We describe how to detect axis shifts by establishing expected ranges for the amplitude of the R-waves in each vector, and declaring an axis shift if the measured R-wave amplitude consistently falls outside of the expected range.
In another preferred feature, we normalize the measured ST deviations from the isoelectric point by the R-wave amplitude. Traditionally, ST deviations are measured in micro-volts (or millimeters on a standard strip chart). 100 micro-volts deviation of the ST segments is considered to be significant in the art of external (surface) ST segment deviation measurements. For an implanted device, the amplitudes of the ECG or EGM are quite different than surface ECG amplitudes. Rather than calibrate each patient""s device to absolute voltage units, and derive some new significance threshold for ST changes in an implanted device, our approach has been to prefer normalization of the ST change by the R-wave amplitude makes common thresholds (i.e., 10%) applicable to all patients. (This has a multidimensional aspect as well, as the R-wave amplitude and ST deviation can be vectors, and the vector deviation of the ST segment form the isoelectric baseline can be normalized by the magnitude of the R-wave).
We also prefer to look for a positive and a negative peak after sensing that we have found an R-wave. We then compare them and choose the larger absolute valued one as the R-peak. To reduce cost or complexity, this feature may only used during setup to account for polarity switching, and then once the orientation of the R-wave is known, the first or second peak may also be chosen as the R-peak sample. It is preferrable to periodically or continually check employ this feature to be sure there is not a change in direction, however.
In another preferred feature, we provide detection of ischemia in the presence of paced ventricular rhythm. If the rhythm includes ventricular pacing the QRST morphology is distorted and standard measurements of ST segment are inaccurate for detection of ischemia. In some forms of the present invention, sporadic ventricular pacing is ignored and ST measurements are conducted (i.e., the signal is sampled) only on intrinsic beats. In the presence of consistent ventricular pacing, ischemia is detected by temporarily modifying the pacing rate (if possible) to let the ST measurements be obtained at a consistent paced rate. For example, for every minute of paced ventricular rhythm, the pacing rate would be set to 70 bpm for a period of for example, 3 beats. The ST segment and isoelectric segment measurements can them be made at these same rate paced beats. This could be done about once each minute. For the algorithm discussed within, the average Rxe2x80x94R interval would be that of the 3 paced beat rate.
Pacing and intrinsic beat ischemia detection can be employed together, and there is some variability available in providing the most useful algorithm for ischemia detection in the presence of pacing which we described in detail within.
An alternative for using the other features of this invention during pacing is to use consistent pacing timing but adopt the pacing spike as the fiducial point and the times of measurement of the ST segment will then be at a constant delay from the delivery of the pacing stimulus. In other words, substitute the pacing pulse for the R-wave peak for the peak for the rest of the decisions.